Plot a simple scatter plot graph with two additional solid lines

Is there any way for me to reduce the number of lines to achieve exactly the same outcome?

should, in isolation, not be your overriding concern, and your code is about as minimally chunky as matplotlib will allow. Your current push - rather than to shed a line or two - should be to increase static testability, maintainability and structure. Said another way, this is not code golf, and not all short code is good code.

To that end:

• Do not enforce a style in the global namespace - only call that from a routine in the application. What if someone else wants to import and reuse parts of your code?
• Add PEP484 type hints.
• Avoid calling gca and gcf. It's easy, and preferable, to have local references to your actual figure and axes upon creation, and to use methods bound to those specific objects instead of plt. Function calls via plt have more visual ambiguity, and need to infer the current figure and axes; being explicit is a better idea. On top of that, calls to plt are just wrappers to the bound instance methods anyway.
• Choose a consistent quote style. black prefers double quotes but I have a vendetta against black and personally prefer single quotes. It's up to you.
• Do not force a show() in the call to plot_returns, and return the generated Figure instead of None. This will improve reusability and testability.
• Do not use strings for internal date logic. Even if you had to use strings, prefer an unambiguous YYYY-mm-dd ISO format instead of yours.
• np.random.random is deprecated; use default_rng() instead.

Suggested

from datetime import date

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.figure import Figure


def plot_returns(
    dates: pd.DatetimeIndex,
    return_values: np.ndarray,
    ewma_values: np.ndarray,
    main_label: str,
) -> Figure:
    fig, ax = plt.subplots(figsize=(15, 10))

    ax.scatter(dates, return_values, linestyle='-', color='blue', s=3, label='Daily Returns')
    ax.plot(dates, ewma_values, linestyle='-', color='green', label='EWMA')

    fig.autofmt_xdate()
    
    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
    ax.xaxis.set_major_locator(mdates.DayLocator(interval=31))
    ax.set_xlabel('Day', fontsize=14)
    ax.set_ylabel('Return', fontsize=14)
    ax.set_title(main_label, fontsize=14)
    ax.legend(loc='upper right', facecolor='white', edgecolor='black', framealpha=1, ncol=1, fontsize=12)
    ax.set_xlim(left=min(dates))

    return fig


def main() -> None:
    dates = pd.date_range(start=date(2018, 1, 1), end=date(2018, 10, 10))
    rand = np.random.default_rng()
    return_values = rand.random(len(dates))
    ewma_values = rand.uniform(low=0.5, high=0.6, size=len(dates))

    plt.style.use('ggplot')
    plot_returns(dates, return_values, ewma_values, 'Example')
    plt.show()


if __name__ == '__main__':
    main()